This presentation will provide an outline of a framework supporting Assistive Technology (AT) selection in three stages, and the results of initial validation testing in Europe. The ultimate goal is to enhance individuals’ participation in society by providing AT solutions that match the needs of the user.
Assistive Technology is increasingly used as an intervention to support individuals’ participation in society. The adoption of technology in health and disability is influenced by health care systems, technological advances, and public expectations. Health and social services are continually working toward goals of evidence-based practice, efficient and cost-effective solutions that result in measurable improvements in functioning and consumer satisfaction. AT has the potential to deliver in these areas if supported by a coherent clinical reasoning process.
The ICF was developed by the World Health Organisation (WHO) and endorsed as a common language for describing health and disability. It has been adopted by many countries in health policy and service delivery, however the clinical applications are still developing and practitioners may benefit from guidance in applying the framework. The ISO 9999 is a classification of technical aids for persons with disabilities, and forms part of the WHO’s family of International Classifications. It has been adopted by some health insurance companies and online AT databases to index assistive technologies.
This study is part of the MURINET (Multidisciplinary Research Network on Health and Disability in Europe), which aims to support the EU in adopting an ICF-based holistic and interdisciplinary approach to health and disability. It follows on from two earlier studies, a literature review and a survey of European practitioners, which indicated a need for evidence-based procedures for AT advising and selection to increase consumer satisfaction and efficiency. The project aims to support practitioners working with AT users in a structured, goal-directed way to consider the critical factors predicting a match between user and technology, and improve the effectiveness of AT interventions in rehabilitation.
The framework being presented was developed based on a review of relevant literature and existing AT databases and tools. It is divided in to three stages: